1. Field of the Invention
This application relates to information storage retrieval systems. More particularly, this application relates to a system for retrieving playable videos related to a search query object and displaying those results in a video playlist to a user.
2. Description of the Related Art
Phrase based or keyword searching is a common method of searching used for electronic data. Keyword searching searches throughout an information database for instances of the words in the search query. Keyword searching does not, however, give results based on relevance; search query results often include items with no relevance or relationship to one another other than the instance of a word in the search query. For example, a user intending to search products by the technology company APPLE may enter the search query “Apple.” The search results, however, would likely include items relating to the apple fruit, songs by the music label Apple, and so on. Consequently, the search query results of phrase based searching often have nothing in common with the user's search intent.
Search methods which relate one object to another object are often used in place of keyword searching in order to provide search query results relevant to the searcher's intent. Such relationship-based search methods vary widely and range from precise to general catch-all approaches. Methods relating text objects can vary widely in precision and approach, quality and quantity. For example, Caid et al., in U.S. Pat. No. 5,619,709, titled “System and Method of Context Vector Generation and Retrieval” relies on context vector generations and dated neural network approaches as opposed to more advanced auto-associative approaches. Weissman et al, in U.S. Pat. No. 6,816,857, uses methods of distance calculation to determine relationships for the purpose of placing meaning-based advertising on websites or to rate document relevance in currently used search engines.
These relationship based searches do not, however simulate the process that a human would use in analyzing relevant information to relate objects with one another. Starting with an object of interest, a researcher typically researches within certain contexts and forms relationships between information gathered during the process of reading and analyzing literature. During this flexible process, the context of interest may change, become refined or shift and take on a new direction depending on the information found or thought processes of the researcher. After the researcher finishes the research process, he is left with a valuable collection of information that is related to a specific theme or context of interest. For example, if the researcher's object of interest was a period of music and the context was the Baroque style, then a researcher might relate compositions to one another, compositions to a composer, compositions to a geographical location or time period. Common relationship-based searches do not simulate this process because they are both inflexible and non-interactive; they neither allow a user to define and control the context and individual relationships during the search, nor do they allow for the quality and quantity of relationships to be determined and visualized interactively by the user.
Furthermore, these systems do not identify playable media related to the user query object that may have hidden relationships or that are not directly related to with the query object. Additionally, these searches do not ideally present retrieved playable media. For example, key word and relationship based searches may return videos or media related to a user query as an alternative to returning web page results. However, the media results are based on direct relationships to the query term itself and may not reveal hidden relationships or highlight contextual relationships to the query term. Thus, information corresponding to hidden relationships between the query object and the playable media that may be useful to a user is not available using these search techniques.